Rates and costs of respiratory illness in coal mining: a cross-industry comparative analysis.

OBJECTIVE: To estimate the prevalence and costs of respiratory illness for workers in coal mining, compared with other US industries. METHODS: Using 5 years of insurance claims data for an annual average of 96,240 adult males, we model the probability and costs of respiratory illness as a function of workers' industry and other factors. RESULTS: Controlling for nonindustry factors, workers in coal mining had significantly higher rates of respiratory illness claims (by 2.1% to 3.3% points) compared with other mining, agriculture, construction, and manufacturing. For coal mining workers with respiratory illness, annual medical care costs for these claims were also significantly higher (by $111 to $289). Surprisingly, drug costs were mostly lower (by $17 to $268). CONCLUSIONS: Our findings underscore the continued importance and potential cost effectiveness of measures to protect miners from harmful occupational exposures, particularly to coal dust.

Mammography facilities are accessible, so why is utilization so low?

OBJECTIVE: This study examines new socio-ecological variables reflecting community context as predictors of mammography use. METHODS: The conceptual model is a hybrid of traditional health-behavioral and socio-ecological constructs with an emphasis on spatial interaction among women and their environments, differentiating between several levels of influence for community context. Multilevel probability models of mammography use are estimated. The study sample includes 70,129 women with traditional Medicare fee-for-service coverage for inpatient and outpatient services, drawn from the SEER-Medicare linked data. The study population lives in heterogeneous California, where mammography facilities are dense but utilization rates are low. RESULTS: Several contextual effects have large significant impacts on the probability of mammography use. Women living in areas with higher proportions of elderly in poverty are 33% less likely to use mammography. However, dually eligible women living in these poor areas are 2% more likely to use mammography than those without extra assistance living in these areas. Living in areas with higher commuter intensity, higher violent crime rates, greater land use mix (urbanicity), or more segregated Hispanic communities exhibit -14%, -1%, -6%, and -3% (lower) probability of use, respectively. Women living in segregated American Indian communities or in communities where more elderly women live alone exhibit 16% and 12% (higher) probability of use, respectively. Minority women living in more segregated communities by their minority are more likely to use mammography, suggesting social support, but this is significant for Native Americans only. Women with disability as their original reason for entitlement are found 40% more likely to use mammography when they reside in communities with high commuter intensity, suggesting greater ease of transportation for them in these environments. CONCLUSIONS: Socio-ecological variables reflecting community context are important predictors of mammography use in insured elderly populations, often with larger magnitudes of effect than personal characteristics such as race or ethnicity (-3% to -7%), age (-2%), recent address change (-7%), disability (-5%) or dual eligibility status (-1%). Better understanding of community factors can enhance cancer control efforts.

Heterogeneity in mammography use across the nation: separating evidence of disparities from the disproportionate effects of geography.

BACKGROUND: Mammography is essential for early detection of breast cancer and both reduced morbidity and increased survival among breast cancer victims. Utilization is lower than national guidelines, and evidence of a recent decline in mammography use has sparked concern. We demonstrate that regression models estimated over pooled samples of heterogeneous states may provide misleading information regarding predictors of health care utilization and that comprehensive cancer control efforts should focus on understanding these differences and underlying causal factors. Our study population includes all women over age 64 with breast cancer in the Surveillance Epidemiology and End Results (SEER) cancer registries, linked to a nationally representative 5% reference sample of Medicare-eligible women located in 11 states that span all census regions and are heterogeneous in racial and ethnic mix. Combining women with and without cancer in the sample allows assessment of previous cancer diagnosis on propensity to use mammography. Our conceptual model recognizes the interplay between individual, social, cultural, and physical environments along the pathways to health care utilization, while delineating local and more distant levels of influence among contextual variables. In regression modeling, we assess individual-level effects, direct effects of contextual factors, and interaction effects between individual and contextual factors. RESULTS: Pooling all women across states leads to quite different conclusions than state-specific models. Commuter intensity, community acculturation, and community elderly impoverishment have significant direct impacts on mammography use which vary across states. Minorities living in isolated enclaves with others of the same race/ethnicity may be either advantaged or disadvantaged, depending upon the place studied. CONCLUSION: Careful analysis of place-specific context is essential for understanding differences across communities stemming from different causal factors. Optimal policy interventions to change behavior (improve screening rates) will be as heterogeneous as local community characteristics, so no "one size fits all" policy can improve population health. Probability modeling with correction for clustering of individuals within multilevel contexts can reveal important differences from place to place and identify key factors to inform targeting of specific communities for further study.

High-risk individuals' willingness to pay for diabetes risk-reduction programs.

OBJECTIVE: The purpose of this study was to estimate how much at-risk individuals are willing to pay for type 2 diabetes primary prevention programs. RESEARCH DESIGN AND METHODS: An Internet-based, choice-format conjoint survey was presented to individuals at elevated risk for type 2 diabetes. Hypothetical diabetes risk-reduction programs included seven features: diet, exercise, counseling, medication, weight loss goal, risk reduction, and program costs. The sample included 582 individuals aged > or =45 years, two-thirds of whom were obese. Conditional logit models were used to calculate participants' willingness to pay for risk reduction programs. Each respondent's self-assessed risk of developing diabetes was compared with an objective measure based on a diabetes screening tool. RESULTS: Many respondents underestimated their personal risk of developing diabetes. Those with a low perceived risk were less likely to indicate that they would participate in a diabetes prevention program. Individuals had the strongest preference for programs with large weight loss goals, fewer restrictions on diet, and larger reductions in the risk of diabetes. Respondents were willing to pay approximately $1,500 over 3 years to participate in a lifestyle intervention program similar to the Diabetes Prevention Program. Individuals with a high perceived risk were willing to pay more than individuals with lower perceived risk. CONCLUSIONS: Many individuals will be willing to participate in interventions to delay or prevent diabetes if the interventions are subsidized, but most will be unwilling to pay the full program cost. Our results also offer insights for designing risk-reduction programs that appeal to potential participants.